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Patient ancestry significantly contributes to molecular heterogeneity of systemic lupus erythematosus
Michelle D. Catalina, … , Amrie C. Grammer, Peter E. Lipsky
Michelle D. Catalina, … , Amrie C. Grammer, Peter E. Lipsky
Published August 6, 2020
Citation Information: JCI Insight. 2020;5(15):e140380. https://doi.org/10.1172/jci.insight.140380.
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Research Article

Patient ancestry significantly contributes to molecular heterogeneity of systemic lupus erythematosus

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Abstract

Gene expression signatures can stratify patients with heterogeneous diseases, such as systemic lupus erythematosus (SLE), yet understanding the contributions of ancestral background to this heterogeneity is not well understood. We hypothesized that ancestry would significantly influence gene expression signatures and measured 34 gene modules in 1566 SLE patients of African ancestry (AA), European ancestry (EA), or Native American ancestry (NAA). Healthy subject ancestry-specific gene expression provided the transcriptomic background upon which the SLE patient signatures were built. Although standard therapy affected every gene signature and significantly increased myeloid cell signatures, logistic regression analysis determined that ancestral background significantly changed 23 of 34 gene signatures. Additionally, the strongest association to gene expression changes was found with autoantibodies, and this also had etiology in ancestry: the AA predisposition to have both RNP and dsDNA autoantibodies compared with EA predisposition to have only anti-dsDNA. A machine learning approach was used to determine a gene signature characteristic to distinguish AA SLE and was most influenced by genes characteristic of the perturbed B cell axis in AA SLE patients.

Authors

Michelle D. Catalina, Prathyusha Bachali, Anthony E. Yeo, Nicholas S. Geraci, Michelle A. Petri, Amrie C. Grammer, Peter E. Lipsky

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Figure 1

Individual SLE patients manifest varied patterns of signatures for 34 cell and process modules.

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Individual SLE patients manifest varied patterns of signatures for 34 ce...
(A) GSVA was carried out on 17 female HC to determine the mean and SD of control GSVA scores for 34 cell type and process modules. HC mean scores ± 1 SD were used to determine a normal range for GSVA scores. SLE female patient (GSE88884 ILL1 and ILL2 data set cohorts; n = 1566) GSVA scores were determined and compared with HC values to determine whether patients had increased (+1), decreased (–1), or normal (zero) values. GSVA enrichment gene symbols for each module are in Supplemental Table 5. (B and C) Percentage of patients within each ancestry (AA, n = 216; NAA, n = 232; EA, n = 1118) with > 1 (B) or < 1 (C) SD GSVA scores for each cell type and process module. Fisher’s exact P < 0.05 are indicated by different color asterisk: black asterisks for comparisons between all 3, red asterisks between NAA and AA/EA, orange asterisks between NAA and EA, light blue asterisks between AA and EA, and dark blue asterisks between AA and NAA/EA. Exact P values and percentages are listed in Supplemental Table 6. (D) WGCNA was carried out on data set GSE88884 ILL1 and ILL2 cohorts separately. Pearson correlation r values to ancestry were determined for each module and listed if P < 0.05.

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